Hao Cheng
Hao Cheng
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Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
H Cheng, Z Zhu, X Li, Y Gong, X Sun, Y Liu
ICLR 2021 arXiv preprint arXiv:2010.02347, 2020
Learning with noisy labels revisited: A study using real-world human annotations
J Wei, Z Zhu, H Cheng, T Liu, G Niu, Y Liu
arXiv preprint arXiv:2110.12088, 2021
Asymmetric co-teaching for unsupervised cross-domain person re-identification
F Yang, K Li, Z Zhong, Z Luo, X Sun, H Cheng, X Guo, F Huang, R Ji, S Li
Proceedings of the AAAI conference on artificial intelligence 34 (07), 12597 …, 2020
Pruning Filter in Filter
F Meng, H Cheng, K Li, H Luo, X Guo, G Lu, X Sun
NeurlPS 2020, arXiv preprint arXiv:2009.14410, 2020
Removing the background by adding the background: Towards background robust self-supervised video representation learning
J Wang, Y Gao, K Li, Y Lin, AJ Ma, H Cheng, P Peng, F Huang, R Ji, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment
Y Liu, Y Yao, JF Ton, X Zhang, RGH Cheng, Y Klochkov, MF Taufiq, H Li
arXiv preprint arXiv:2308.05374, 2023
Do not disturb me: Person re-identification under the interference of other pedestrians
S Zhao, C Gao, J Zhang, H Cheng, C Han, X Jiang, X Guo, WS Zheng, ...
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Filter grafting for deep neural networks
F Meng, H Cheng, K Li, Z Xu, R Ji, X Sun, G Lu
CVPR 2020, 6599-6607, 2020
DisCo: Remedying Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning
Y Gao, JX Zhuang, S Lin, H Cheng, X Sun, K Li, C Shen
European Conference on Computer Vision, 237-253, 2022
Evaluating capability of deep neural networks for image classification via information plane
H Cheng, D Lian, S Gao, Y Geng
ECCV 2018, 168-182, 2018
Mitigating memorization of noisy labels via regularization between representations
H Cheng, Z Zhu, X Sun, Y Liu
arXiv preprint arXiv:2110.09022, 2021
Identifiability of label noise transition matrix
Y Liu, H Cheng, K Zhang
International Conference on Machine Learning, 21475-21496, 2023
On the consistency training for open-set semi-supervised learning
H Luo, H Cheng, Y Gao, K Li, M Zhang, F Meng, X Guo, F Huang, X Sun
arXiv preprint arXiv:2101.08237 3 (6), 2021
Local to global learning: Gradually adding classes for training deep neural networks
H Cheng, D Lian, B Deng, S Gao, T Tan, Y Geng
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
One for more: Selecting generalizable samples for generalizable ReID model
E Zhang, X Jiang, H Cheng, A Wu, F Yu, K Li, X Guo, F Zheng, W Zheng, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (4), 3324-3332, 2021
RMNet: Equivalently Removing Residual Connection from Networks
F Meng, H Cheng, J Zhuang, K Li, X Sun
arXiv preprint arXiv:2111.00687, 2021
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
Z Zhu, J Wang, H Cheng, Y Liu
arXiv preprint arXiv:2311.11202, 2023
Filter Grafting for Deep Neural Networks: Reason, Method, and Cultivation
H Cheng, F Meng, K Li, Y Gao, G Lu, X Sun, R Ji
arXiv preprint arXiv:2004.12311, 2020
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
H Cheng, Q Wen, Y Liu, L Sun
arXiv preprint arXiv:2402.02032, 2024
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